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통계로 알아보는 정보보호 - 2009년에는 어떤 일들이 일어날까 -2008년 침해사고 동향 및 2009년 전망
박진완,Park, Jin-Wan 한국정보보호진흥원 2009 정보보호뉴스 Vol.136 No.-
KISA 인터넷침해사고대응지원센터가 지난 1월 '2008년 침해사고 동향 및 2009년 전망'을 발표했다. 침해사고 동향을 분석하고 향후 등장할 위협을 예측하는 이 보고서는 국내외 정보보호 분야의 기술 지형을 한눈에 보여준다는 점에서 큰 의미를 지니고 있다. 웜 바이러스와 악성 봇 분야의 주요내용을 중심으로 2008년 침해사고 동향과 2009년을 전망해 본다.
한국인 조현병 환자에서 Chromogranin B 유전자와 안구운동 이상의 연합에 대한 연구
박진완,백두현,황민규,이민지,신형두,신태민,한상우,황재욱,이연정,우성일,Park, Jin Wan,Pak, Doo Hyun,Hwang, Min Gyu,Lee, Min Ji,Shin, Hyoung Doo,Shin, Tae-Min,Hahn, Sang Woo,Hwang, Jaeuk,Lee, Yeon Jung,Woo, Sung-Il 대한생물정신의학회 2018 생물정신의학 Vol.25 No.4
Objectives According to previous studies, the Chromogranin B (CHGB) gene could be an important candidate gene for schizophrenia which is located on chromosome 20p12.3. Some studies have linked the polymorphism in CHGB gene with the risk of schizophrenia. Meanwhile, smooth pursuit eye movement (SPEM) abnormality has been regarded as one of the most consistent endophenotype of schizophrenia. In this study, we investigated the association between the polymorphisms in CHGB gene and SPEM abnormality in Korean patients with schizophrenia. Methods We measured SPEM function in 24 Korean patients with schizophrenia (16 male, 8 female) and they were divided according to SPEM function into two groups, good and poor SPEM function groups. We also investigated genotypes of polymorphisms in CHGB gene in each group. A logistic regression analysis was performed to find the association between SPEM abnormality and the number of polymorphism. Results The natural logarithm value of signal/noise ratio (Ln S/N ratio) of good SPEM function group was $4.19{\pm}0.19$ and that of poor SPEM function group was $3.17{\pm}0.65$. In total, 15 single nucleotide polymorphisms of CHGB were identified and the genotypes were divided into C/C, C/R, and R/R. Statistical analysis revealed that two genetic variants (rs16991480, rs76791154) were associated with SPEM abnormality in schizophrenia (p = 0.004). Conclusions Despite the limitations including a small number of samples and lack of functional study, our results suggest that genetic variants of CHGB may be associated with SPEM abnormality and provide useful preliminary information for further study.nwhile, smooth pursuit eye movement (SPEM) abnormality has been regarded as one of the most consistent endophenotype of schizophrenia. In this study, we investigated the association between the polymorphisms in CHGB gene and SPEM abnormality in Korean patients with schizophrenia. MethodsZZWe measured SPEM function in 24 Korean patients with schizophrenia (16 male, 8 female) and they were divided according to SPEM function into two groups, good and poor SPEM function groups. We also investigated genotypes of polymorphisms in CHGB gene in each group. A logistic regression analysis was performed to find the association between SPEM abnormality and the number of polymorphism. ResultsZZThe natural logarithm value of signal/noise ratio (Ln S/N ratio) of good SPEM function group was $4.19{\pm}0.19$ and that of poor SPEM function group was $3.17{\pm}0.65$. In total, 15 single nucleotide polymorphisms of CHGB were identified and the genotypes were divided into C/C, C/R, and R/R. Statistical analysis revealed that two genetic variants (rs16991480, rs76791154) were associated with SPEM abnormality in schizophrenia (p = 0.004). ConclusionsZZDespite the limitations including a small number of samples and lack of functional study, our results suggest that genetic variants of CHGB may be associated with SPEM abnormality and provide useful preliminary information for further study.
박진완,김명섭,Park, Jin-Wan,Kim, Myung-Sup 한국정보처리학회 2011 정보처리학회논문지 C : 정보통신,정보보안 Vol.18 No.4
네트워크의 고속화와 다양한 서비스의 등장으로 오늘날의 네트워크 트래픽은 복잡 다양해지고 있다. 효율적인 네트워크 관리를 위해서는 네트워크에서 발생하는 트래픽에 대한 다양한 분석이 필요하다. QoS, SLA와 같은 정책을 적용하기 위해서는 트래픽 분석 중에서도 트래픽 분류의 중요성이 크다. 현재까지 트래픽 분류에 관한 연구가 활발히 진행되어 왔는데 최근에는 플로우의 통계 정보를 이용한 트래픽 분류 방법론이 많이 연구되고 있다. 본 논문에서는 기존 연구에서 제안한 페이로드 크기 분포를 이용한 트래픽 분류 방법의 문제점인 낮은 분석률 및 정확도를 향상시키는 방법을 제안한다. 본 논문에서 제안하는 방법은 PSD 충돌로 인해 분류하지 못하는 트래픽을 IP와 port정보를 이용하여 추가적으로 분류하여 분석률을 향상시키고 기존 분류 방법에서 트래픽 분류를 위해 사용되던 플로우와 시그니쳐 사이의 거리 측정 방법을 벡터 거리 측정에서 패킷 별 거리 측정으로의 변경으로 통해 분류 방법의 정확도를 향상시킨다. 제안한 방법은 학내 망에서의 실험을 통해 기존 알고리즘에 비해 향상된 알고리즘의 성능을 검증한다. Nowadays, the traffic type and behavior are extremely diverse due to the appearance of various services on Internet, which makes the need of traffic identification important for efficient operation and management of network. In recent years traffic identification methodology using statistical features of flow has been broadly studied. We also proposed a traffic identification methodology using payload size distribution in our previous work, which has a problem of low completeness. In this paper, we improved the completeness by solving the PSD conflict using IP and port. And we improved the accuracy by changing the distance measurement between flow and statistic signature from vector distance to per-packet distance. The feasibility of our methodology was proved via experimental evaluation on our campus network.